More than 400,000 newborns delivered each year in the U.S. require admission to neonatal intensive care units (NICUs). Many of these infants later develop substantial neurologic morbidity. Our long-term hypothesis is that the NICU sensory environment, which differs dramatically from the in utero milieu, disrupts the stimulus- sensitive plasticity of the immature brain and contributes to abnormal developmental outcome, at least in some vulnerable infants. Healthy newborns generate sleep, a complex and highly regulated neurologic function, for two-thirds of each day. Emerging evidence suggests that disturbed sleep physiology during late infancy contributes to subsequent adverse neurobehavioral outcomes. Sleep is rarely analyzed in sick neonates, in part because of a key unsolved challenge: a practical, validated, and quantitative approach to monitoring neonatal sleep cycling has not been established. Innovative preliminary work by the investigators now suggests that several quantitative sleep measures - sleep/wake bout lengths, sleep fragmentation (entropy), and stage transition probabilities - may predict neurologic status. Yet, the optimal environment to promote ideal neonatal sleep is unknown. Compelling recent data highlight the complexities inherent in efforts to optimize the NICU environment. Preterm infants protected from extrinsic sound, to minimize sleep disruption, showed poor language development. Conversely, increased language exposure in the NICU led to better long-term language development. Therefore, simple provision of a quiet NICU environment may not be an ideal therapeutic approach. In this setting, the research now proposed is guided by the following Global Hypothesis: For neonates, normal quality and quantity of sleep contribute to optimal neurodevelopment, but sleep is disrupted in the NICU by potentially modifiable environmental noise. Aim 1: Characterize the above novel quantitative sleep measures as a function of gestational age and postnatal age, adjusted for illness severity, among 50 late-preterm and term NICU patients. Aim 2: Determine the sensitivity of these quantitative sleep measures to non-language noise, conversation, and periods of silence, quantified by automated language environment analysis (LENA) testing during polysomnography. Aim 3: Assess the effect of enriched exposure to mother's speech, as opposed to non-language noise, on neonatal sleep, as measured by sleep/wake bout lengths, entropy, and stage transition probabilities. Application of formal PSG in the NICU, with innovative analytic techniques to assess sleep stage distribution and sleep fragmentation, will provide novel, objective measures of neonatal brain functional integrity. The proposed study will be the first to assess the influence of the NICU acoustic environment on quantitative PSG data. Results will inform the subsequent design of interventions to optimize the NICU acoustic environment, ameliorate sleep regulation, and improve neurodevelopmental outcomes.